利用核糖体定位数据发现人类疟疾寄生虫中的新基因

N Pokhriyal, N Ponts, E Y Harris, K G Le Roch, S Lonardi
{"title":"利用核糖体定位数据发现人类疟疾寄生虫中的新基因","authors":"N Pokhriyal, N Ponts, E Y Harris, K G Le Roch, S Lonardi","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Recent genome-wide studies on nucleosome positioning in model organisms have shown strong evidence that nucleosome landscapes in the proximity of protein-coding genes exhibit regular characteristic patterns. Here, we propose a computational framework to discover novel genes in the human malaria parasite genome <i>P. falciparum</i> using nucleosome positioning inferred from MAINE-seq data. We rely on a classifier trained on the nucleosome landscape profiles of experimentally verified genes, and then used to discover new genes (without considering the primary DNA sequence). Cross-validation experiments show that our classifier is very accurate. About two thirds of the locations reported by the classifier match experimentally determined expressed sequence tags in GenBank, for which no gene has been annotated in the human malaria parasite.</p>","PeriodicalId":72665,"journal":{"name":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","volume":"9 ","pages":"124-135"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4112967/pdf/nihms504365.pdf","citationCount":"0","resultStr":"{\"title\":\"Novel Gene Discovery in the Human Malaria Parasite using Nucleosome Positioning Data.\",\"authors\":\"N Pokhriyal, N Ponts, E Y Harris, K G Le Roch, S Lonardi\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Recent genome-wide studies on nucleosome positioning in model organisms have shown strong evidence that nucleosome landscapes in the proximity of protein-coding genes exhibit regular characteristic patterns. Here, we propose a computational framework to discover novel genes in the human malaria parasite genome <i>P. falciparum</i> using nucleosome positioning inferred from MAINE-seq data. We rely on a classifier trained on the nucleosome landscape profiles of experimentally verified genes, and then used to discover new genes (without considering the primary DNA sequence). Cross-validation experiments show that our classifier is very accurate. About two thirds of the locations reported by the classifier match experimentally determined expressed sequence tags in GenBank, for which no gene has been annotated in the human malaria parasite.</p>\",\"PeriodicalId\":72665,\"journal\":{\"name\":\"Computational systems bioinformatics. Computational Systems Bioinformatics Conference\",\"volume\":\"9 \",\"pages\":\"124-135\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4112967/pdf/nihms504365.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational systems bioinformatics. Computational Systems Bioinformatics Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational systems bioinformatics. Computational Systems Bioinformatics Conference","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

最近关于模式生物核糖体定位的全基因组研究有力地证明,蛋白编码基因附近的核糖体景观表现出规律性的特征模式。在这里,我们提出了一个计算框架,利用从 MAINE-seq 数据中推断出的核糖体定位发现人类疟原虫基因组恶性疟原虫中的新基因。我们依靠的是根据实验验证基因的核糖体分布图训练的分类器,然后用来发现新基因(不考虑主 DNA 序列)。交叉验证实验表明,我们的分类器非常准确。分类器报告的位置中约有三分之二与 GenBank 中经实验确定的表达序列标签相匹配,而人类疟原虫中还没有基因被注释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

摘要图片

摘要图片

分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Novel Gene Discovery in the Human Malaria Parasite using Nucleosome Positioning Data.

Recent genome-wide studies on nucleosome positioning in model organisms have shown strong evidence that nucleosome landscapes in the proximity of protein-coding genes exhibit regular characteristic patterns. Here, we propose a computational framework to discover novel genes in the human malaria parasite genome P. falciparum using nucleosome positioning inferred from MAINE-seq data. We rely on a classifier trained on the nucleosome landscape profiles of experimentally verified genes, and then used to discover new genes (without considering the primary DNA sequence). Cross-validation experiments show that our classifier is very accurate. About two thirds of the locations reported by the classifier match experimentally determined expressed sequence tags in GenBank, for which no gene has been annotated in the human malaria parasite.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Novel Gene Discovery in the Human Malaria Parasite using Nucleosome Positioning Data. Estimating support for protein-protein interaction data with applications to function prediction. On the accurate construction of consensus genetic maps. Efficient haplotype inference from pedigrees with missing data using linear systems with disjoint-set data structures. Knowledge representation and data mining for biological imaging.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1